2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)最新文献_第5页

Distributed Algorithm for Solving Sylvester Matrix Equation via Iterative Learning Control 基于迭代学习控制的求解Sylvester矩阵方程的分布式算法

2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10166228

Cong Liang, Xuanmin Huo, Shizhou Xu, Lei Wang, Juntao Li

{"title":"Distributed Algorithm for Solving Sylvester Matrix Equation via Iterative Learning Control","authors":"Cong Liang, Xuanmin Huo, Shizhou Xu, Lei Wang, Juntao Li","doi":"10.1109/DDCLS58216.2023.10166228","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10166228","url":null,"abstract":"As the most fundamental type of matrix equation, the Sylvester equation has been widely applied in control theory, signal processing, and many other scientific fields in recent years. The traditional method for solving the Sylvester equation is to transform it into a linear algebraic equation (LAE). However, this method will lead to an increase in the dimension of the coefficient matrix, which makes it difficult to solve the LAE. To alleviate the above problem, a distributed algorithm for solving the Sylvester equation is presented in this paper. Firstly, we obtain a LAE equivalent to the Sylvester equation by utilizing vectorization operation and Kronecker product. Then, a group of agents in the multi-agent system is considered to implement the distributed solution for LAE, where each agent only solves its local task by constantly exchanging information with its neighbors. By constructing the iterative learning control system, a discrete linear system about the tracking error of the agent is obtained. Based on the average neighbor information and the feedback control design, an updating rule for each agent iteratively updating its state is obtained. It is shown that all agents converge to the vectorization solution of the Sylvester equation when the communication topology between agents is undirected complete graph. Finally, a simulation example is provided to demonstrate the effectiveness of the proposed distributed algorithm.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115394002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Line of sight-based MFAC path-following control of underactuated surface vessels with exact sideslip compensation 基于视线的欠驱动水面舰船MFAC路径跟踪控制及精确侧滑补偿

2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10166529

Zhuofu Liu, Qiuxia Zhang, Yongpeng Weng

引用次数: 0

Distributed Bipartite Consensus for Multi-Agent Systems Via Data-Driven Sliding Mode Scheme 基于数据驱动滑模的多智能体系统分布式二部一致性

2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10166623

Huarong Zhao, Li Peng, Linbo Xie, Jielong Yang, Ye Xu

{"title":"Distributed Bipartite Consensus for Multi-Agent Systems Via Data-Driven Sliding Mode Scheme","authors":"Huarong Zhao, Li Peng, Linbo Xie, Jielong Yang, Ye Xu","doi":"10.1109/DDCLS58216.2023.10166623","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10166623","url":null,"abstract":"This paper investigates a fully distributed bipartite consensus tracking problem for nonlinear discrete-time Multi-agent systems (MASs) with unknown dynamics and antagonistic interactions. A fully distributed data-driven sliding mode bipartite consensus (DSMBC) approach is proposed. The convergence of the proposed method is no longer related to the format of the reference trajectory, including time-varying and time-invariant trajectories. Moreover, the strongly connected requirement is no longer needed. Firstly, a bipartite combined measurement error function is formulated to transfer the bipartite consensus issue into the consensus issue. Then, an enhanced compact form dynamic linearization data mode is established by employing the input/output data of the MASs. After that, the DSMBC is constructed, and the proposed algorithm's convergence is proved, showing that each agent's bipartite consensus tracking error is cut to a small region around the origin. Finally, two examples are presented, and the results further demonstrate the correctness and effectiveness of the proposed scheme, where the MASs can tackle both time-varying and time-invariant tracking tasks.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115855796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Substation helmet detection based on improved YOLOX-S algorithm 基于改进YOLOX-S算法的变电站安全帽检测

2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10167037

Xiaodong Tong, Zhaofei Li

{"title":"Substation helmet detection based on improved YOLOX-S algorithm","authors":"Xiaodong Tong, Zhaofei Li","doi":"10.1109/DDCLS58216.2023.10167037","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10167037","url":null,"abstract":"The improved YOLOX-S algorithm is proposed for the detection of small helmet targets based on an improved YOLOX-S algorithm for the detection of helmets worn by relevant personnel in hazardous scenarios in substations. First, the ECA attention mechanism is introduced into the CSPLayer structure in YOLOX-S to direct the model to pay more attention to channel features of small target information and enhance the model's ability to utilize useful features. Secondly, the addition of the ConvNext Block module after the three feature layers of the backbone feature extraction network to enhance the model's ability to exploit useful features. Finally, the weighted feature fusion mechanism of BiFPN is introduced in the enhanced feature extraction network by changing the original concat to BiFPN_concat, adding learnable weights to each input feature to learn the importance of different input features, distinguishing the importance of different features in the feature fusion process, and better focusing on the target information to be detected. The experimental results show that the mAP of the improved algorithm is 92.65%, which is an average accuracy improvement of 2.55% over the original YOLOX-S algorithm and meets the practical requirements.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114317691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive Sliding Mode Control of Suppressing Quadrotor Payload Swing with Variable-Length Cable 变长电缆抑制四旋翼载荷摆动的自适应滑模控制

2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10165786

Yikun Wang, Dazi Li, Jingwen Huang

引用次数: 0

Research on Dissolved Oxygen Fuzzy Controller in Sewage Treatment Process 污水处理过程溶解氧模糊控制器的研究

2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10166801

Zhiguo Lv

引用次数: 0

Time-varying Formation Control for Second-order Nonlinear Multi-UAV System 二阶非线性多无人机系统的时变编队控制

2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10167146

Zhenyan Li, Chunxi Yang, Xiufeng Zhang, Yiming Li, Jianquan Yang

引用次数: 0

Q-Learning-based Finite Control Set Model Predictive Control for LCL-Coupled Inverters with Deviated Parameters 基于q -学习的lcl耦合参数偏差逆变器有限控制集模型预测控制

2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10167014

Lei Zhang, Yunjian Peng, Weijie Sun, Jinze Li

引用次数: 0

Adaptive robust control of the continuous-time two-input systems with unknown disturbance based on Q-function 基于q函数的未知扰动连续双输入系统自适应鲁棒控制

2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10166557

Yongfeng Lv, Zhengyu Cui, Minlin Wang

引用次数: 0

Prediction of Aeration Quantity of Biochemical Tank Based on Ensemble Learning Algorithm 基于集成学习算法的生化池曝气量预测

2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2023-05-12 DOI: 10.1109/DDCLS58216.2023.10167181

yuuki tao, Bin Yang, Zhong-Hua Pang, Lan-Zhi Fan

引用次数: 0